Hyperparameter Optimization

Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion AAAI 2019 On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation AAAI 2019 Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning UAI 2019 Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration NeurIPS 2019 Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions ICLR 2019 TAPAS: Train-Less Accuracy Predictor for Architecture Search AAAI 2019 Automating Bayesian optimization with Bayesian optimization NeurIPS 2018 Hyperparameter Optimization for Tracking With Continuous Deep Q-Learning CVPR 2018 Online Learning Rate Adaptation with Hypergradient Descent ICLR 2018 Predicting accuracy on large datasets from smaller pilot data ACL 2018 Probabilistic Matrix Factorization for Automated Machine Learning NeurIPS 2018 Scalable Hyperparameter Transfer Learning NeurIPS 2018 Understanding Short-Horizon Bias in Stochastic Meta-Optimization ICLR 2018 An Empirical Bayes Approach to Optimizing Machine Learning Algorithms NeurIPS 2017 The Parallel Knowledge Gradient Method for Batch Bayesian Optimization NeurIPS 2016 An Efficient Approach for Assessing Hyperparameter Importance ICML 2014 Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images CVPR 2014 Multi-Task Bayesian Optimization NeurIPS 2013 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Algorithms for Hyper-Parameter Optimization NeurIPS 2011 Efficient multiple hyperparameter learning for log-linear models NeurIPS 2007 An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NeurIPS 2006 Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods NeurIPS 2006 Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NeurIPS 2006